Rules of classification from neural networks to aid decision making in granting of bank credit

Rules of classification from neural networks to aid decision making in granting of bank credit

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Article ID: iaor20084536
Country: Brazil
Volume: 27
Issue: 3
Start Page Number: 407
End Page Number: 426
Publication Date: Sep 2007
Journal: Pesquisa Operacional
Authors: , ,
Keywords: neural networks
Abstract:

Credit-risk evaluation is a very important management science problem in the financial analysis area. Neural Networks have received a lot of attention because of their universal approximation property. They have a high predictive accuracy rate, but how they reach their decisions is not easy to understand. In this paper, we present a real-life credit-risk data set and analyzed it using the NeuroRule extraction technique and the software WEKA. The results were considered very satisfactory, reaching more than 80% of accuracy in granting or denying credit on every simulation.

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